Cisco Model-Driven Telemetry and Sensu Integration
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Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
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Input and output integration overview
The Cisco Model-Driven Telemetry (MDT) plugin facilitates the collection of telemetry data from Cisco networking platforms, utilizing gRPC and TCP transport mechanisms. This plugin is essential for users looking to implement advanced telemetry solutions for better insights and operational efficiency.
This plugin writes metrics events to Sensu via its HTTP events API, enabling seamless integration with the Sensu monitoring platform.
Integration details
Cisco Model-Driven Telemetry
Cisco model-driven telemetry (MDT) is designed to provide a robust means of consuming telemetry data from various Cisco platforms, including IOS XR, IOS XE, and NX-OS. This plugin focuses on the efficient transport of telemetry data using either TCP or gRPC protocols, offering flexibility based on the network environment and requirements. The gRPC transport is particularly advantageous as it supports TLS for enhanced security through encryption and authentication. The plugin is compatible with a range of software versions on Cisco devices, enabling organizations to leverage telemetry capabilities across their network operations. It is especially useful for network monitoring and analytics, as it enables real-time data collection directly from Cisco devices, enhancing visibility into network performance, resource utilization, and operational metrics.
Sensu
This plugin writes metrics events to Sensu via its HTTP events API. Sensu is a monitoring system that enables users to collect, analyze, and manage metrics from various components in their infrastructure. The plugin facilitates the integration of Telegraf, a server agent for collecting and reporting metrics, with the Sensu monitoring platform. Users can configure settings such as backend and agent API URLs, API keys for authentication, and optional TLS settings. The plugin’s core functionality is centered around sending metric events, including check and entity specifications, to Sensu, allowing for comprehensive monitoring and alerting. The API reference provides extensive details about the events and metrics structure, ensuring users can efficiently leverage Sensu’s capabilities for observability and incident response.
Configuration
Cisco Model-Driven Telemetry
[[inputs.cisco_telemetry_mdt]]
## Telemetry transport can be "tcp" or "grpc". TLS is only supported when
## using the grpc transport.
transport = "grpc"
## Address and port to host telemetry listener
service_address = ":57000"
## Grpc Maximum Message Size, default is 4MB, increase the size. This is
## stored as a uint32, and limited to 4294967295.
max_msg_size = 4000000
## Enable TLS; grpc transport only.
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Enable TLS client authentication and define allowed CA certificates; grpc
## transport only.
# tls_allowed_cacerts = ["/etc/telegraf/clientca.pem"]
## Define (for certain nested telemetry measurements with embedded tags) which fields are tags
# embedded_tags = ["Cisco-IOS-XR-qos-ma-oper:qos/interface-table/interface/input/service-policy-names/service-policy-instance/statistics/class-stats/class-name"]
## Include the delete field in every telemetry message.
# include_delete_field = false
## Specify custom name for incoming MDT source field.
# source_field_name = "mdt_source"
## Define aliases to map telemetry encoding paths to simple measurement names
[inputs.cisco_telemetry_mdt.aliases]
ifstats = "ietf-interfaces:interfaces-state/interface/statistics"
## Define Property Xformation, please refer README and https://pubhub.devnetcloud.com/media/dme-docs-9-3-3/docs/appendix/ for Model details.
[inputs.cisco_telemetry_mdt.dmes]
# Global Property Xformation.
# prop1 = "uint64 to int"
# prop2 = "uint64 to string"
# prop3 = "string to uint64"
# prop4 = "string to int64"
# prop5 = "string to float64"
# auto-prop-xfrom = "auto-float-xfrom" #Xform any property which is string, and has float number to type float64
# Per Path property xformation, Name is telemetry configuration under sensor-group, path configuration "WORD Distinguished Name"
# Per Path configuration is better as it avoid property collision issue of types.
# dnpath = '{"Name": "show ip route summary","prop": [{"Key": "routes","Value": "string"}, {"Key": "best-paths","Value": "string"}]}'
# dnpath2 = '{"Name": "show processes cpu","prop": [{"Key": "kernel_percent","Value": "float"}, {"Key": "idle_percent","Value": "float"}, {"Key": "process","Value": "string"}, {"Key": "user_percent","Value": "float"}, {"Key": "onesec","Value": "float"}]}'
# dnpath3 = '{"Name": "show processes memory physical","prop": [{"Key": "processname","Value": "string"}]}'
## Additional GRPC connection settings.
[inputs.cisco_telemetry_mdt.grpc_enforcement_policy]
## GRPC permit keepalives without calls, set to true if your clients are
## sending pings without calls in-flight. This can sometimes happen on IOS-XE
## devices where the GRPC connection is left open but subscriptions have been
## removed, and adding subsequent subscriptions does not keep a stable session.
# permit_keepalive_without_calls = false
## GRPC minimum timeout between successive pings, decreasing this value may
## help if this plugin is closing connections with ENHANCE_YOUR_CALM (too_many_pings).
# keepalive_minimum_time = "5m"
Sensu
[[outputs.sensu]]
## BACKEND API URL is the Sensu Backend API root URL to send metrics to
## (protocol, host, and port only). The output plugin will automatically
## append the corresponding backend API path
## /api/core/v2/namespaces/:entity_namespace/events/:entity_name/:check_name).
##
## Backend Events API reference:
## https://docs.sensu.io/sensu-go/latest/api/events/
##
## AGENT API URL is the Sensu Agent API root URL to send metrics to
## (protocol, host, and port only). The output plugin will automatically
## append the correspeonding agent API path (/events).
##
## Agent API Events API reference:
## https://docs.sensu.io/sensu-go/latest/api/events/
##
## NOTE: if backend_api_url and agent_api_url and api_key are set, the output
## plugin will use backend_api_url. If backend_api_url and agent_api_url are
## not provided, the output plugin will default to use an agent_api_url of
## http://127.0.0.1:3031
##
# backend_api_url = "http://127.0.0.1:8080"
# agent_api_url = "http://127.0.0.1:3031"
## API KEY is the Sensu Backend API token
## Generate a new API token via:
##
## $ sensuctl cluster-role create telegraf --verb create --resource events,entities
## $ sensuctl cluster-role-binding create telegraf --cluster-role telegraf --group telegraf
## $ sensuctl user create telegraf --group telegraf --password REDACTED
## $ sensuctl api-key grant telegraf
##
## For more information on Sensu RBAC profiles & API tokens, please visit:
## - https://docs.sensu.io/sensu-go/latest/reference/rbac/
## - https://docs.sensu.io/sensu-go/latest/reference/apikeys/
##
# api_key = "${SENSU_API_KEY}"
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Timeout for HTTP message
# timeout = "5s"
## HTTP Content-Encoding for write request body, can be set to "gzip" to
## compress body or "identity" to apply no encoding.
# content_encoding = "identity"
## NOTE: Due to the way TOML is parsed, tables must be at the END of the
## plugin definition, otherwise additional config options are read as part of
## the table
## Sensu Event details
##
## Below are the event details to be sent to Sensu. The main portions of the
## event are the check, entity, and metrics specifications. For more information
## on Sensu events and its components, please visit:
## - Events - https://docs.sensu.io/sensu-go/latest/reference/events
## - Checks - https://docs.sensu.io/sensu-go/latest/reference/checks
## - Entities - https://docs.sensu.io/sensu-go/latest/reference/entities
## - Metrics - https://docs.sensu.io/sensu-go/latest/reference/events#metrics
##
## Check specification
## The check name is the name to give the Sensu check associated with the event
## created. This maps to check.metadata.name in the event.
[outputs.sensu.check]
name = "telegraf"
## Entity specification
## Configure the entity name and namespace, if necessary. This will be part of
## the entity.metadata in the event.
##
## NOTE: if the output plugin is configured to send events to a
## backend_api_url and entity_name is not set, the value returned by
## os.Hostname() will be used; if the output plugin is configured to send
## events to an agent_api_url, entity_name and entity_namespace are not used.
# [outputs.sensu.entity]
# name = "server-01"
# namespace = "default"
## Metrics specification
## Configure the tags for the metrics that are sent as part of the Sensu event
# [outputs.sensu.tags]
# source = "telegraf"
## Configure the handler(s) for processing the provided metrics
# [outputs.sensu.metrics]
# handlers = ["influxdb","elasticsearch"]
Input and output integration examples
Cisco Model-Driven Telemetry
-
Real-Time Network Monitoring: Utilize the Cisco MDT plugin to collect network performance metrics from Cisco routers and switches. By feeding telemetry data into a visualization tool, network operators can observe traffic trends, bandwidth usage, and error rates in real-time. This proactive monitoring allows teams to swiftly address issues before they affect network performance, resulting in a more reliable service.
-
Automated Anomaly Detection: Integrate Cisco MDT with machine learning algorithms to create an automated anomaly detection system. By continuously analyzing telemetry data, the system can identify deviations from typical operational patterns, providing alerts for unusual conditions that may signify network problems or security threats, which can aid in maintaining operational integrity.
-
Dynamic Configuration Management: Leveraging the telemetry data collected from Cisco devices, organizations can implement dynamic configuration management solutions that automatically adjust network settings based on current performance indicators. For instance, if the telemetry indicates high utilization on certain links, the system could dynamically route traffic to underutilized paths, optimizing resource usage.
-
Enhanced Reporting and Analytics: Use the Cisco MDT plugin to feed detailed telemetry data into analytics platforms, enabling comprehensive reporting on network health and performance. Historical and real-time analysis can guide decision-making and strategic planning, helping organizations to allocate resources more effectively and understand their network’s operational landscape better.
Sensu
-
Real-Time Infrastructure Monitoring: Utilize the Sensu plugin to send performance metrics from various servers and services directly to Sensu. This real-time data flow enables teams to visualize infrastructure health, track resource usage, and receive immediate alerts for any anomalies detected. By centralizing monitoring through Sensu, organizations can create a holistic view of their systems and respond swiftly to issues.
-
Automated Incident Response Workflows: Leverage the plugin to automatically trigger incident response workflows based on the metrics events sent to Sensu. For example, if CPU usage exceeds a defined threshold, the Sensu system can be configured to alert the operations team, which can then initiate automated remediation processes, reducing downtime and maintaining system reliability. This integration allows for proactive management of system resources.
-
Dynamic Scaling of Resources: Use the Sensu plugin to feed metrics into an auto-scaling system that adjusts resources based on demand. By tracking metrics like request load and resource utilization, organizations can automatically scale their infrastructure up or down, ensuring optimal performance and cost efficiency without manual intervention.
-
Centralized Logging and Monitoring: Combine the Sensu with logging tools to send logs and performance metrics to a centralized monitoring system. This comprehensive approach allows teams to correlate logs with metric events, providing deeper insights into system behavior and performance, which aids in troubleshooting and performance optimization over time.
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Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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